Quantitative AI Portfolio Engineer (Fixed Income) H/F

Join Amundi Asset Management as a Quantitative AI Portfolio Engineer specializing in Fixed Income. In this role, you will design and develop quantitative approaches and machine learning algorithms to generate investment signals, perform advanced feature engineering, and integrate alternative and unstructured data. You will also implement robust back-testing frameworks, own the full model lifecycle, and document methodologies and assumptions. The ideal candidate will have an advanced degree in quantitative finance or a related field, strong knowledge of machine learning techniques, and solid understanding of fixed income markets. Fluency in French and professional proficiency in English are required.

• Concevoir et développer des approches quantitatives et des algorithmes d'apprentissage automatique pour générer des signaux d'investissement sur les taux d'intérêt et les marchés du crédit.
• Mettre en œuvre et superviser des cadres de back-testing robustes, effectuer des analyses de robustesse approfondies via des tests de stress, des analyses de marche avant, des méthodes de bootstrap.
• Posséder l'ensemble du cycle de vie du modèle : spécification, prototypage, validation, industrialisation, surveillance et maintenance.

Advanced degree in quantitative finance, financial engineering, applied mathematics, computer science, data science or equivalent.

• Strong knowledge of modern machine learning techniques (neural networks, XGBoost, sequence models such as RNN/LSTM/Transformer, ensemble methods).
• Practical experience in NLP (Transformers (BERT), embeddings, fine-tuning, Clustering, Classification and sentiment analysis) applied to financial text.
• Solid understanding of fixed income markets (yield curve structure, credit spreads, interest-rate derivatives) and portfolio constraints.
• Strong programming skills in Python (Pandas, scikit-learn, hugging face, spaCy, sentence-transformers, PyTorch/TensorFlow, pyspark), SQL. C++/Java knowledge is a plus.
• Familiarity with data engineering tools (Airflow, Spark, Kafka) and cloud platforms (AWS/GCP/Azure) is advantageous.

**· Behavioral Skills**

• Scientific mindset, intellectual curiosity and experimental rigor.
• Ability to synthesize and explain technical results to non-technical audiences.
• Autonomy, initiative and strong collaboration in cross-functional teams.
• Production-oriented mindset with focus on reproducibility and operational robustness.

Fluent in French and professional proficiency in English.